1. Scientific Computing Topics for Final Projects Dr. Guy Tel-Zur Version 2, 15-05-2011

2. Best option Find a computational challenge in your field of research (Math, CS, Biology, Chemistry, Physics…) Think Parallel or Distributed Use advanced Visualization

3. In the next slides are topics which can candidates for the Final Projects

4. Class 1: Science topic + a computational tools Examples: – Map-Reduce Paradigm, http://hadoop.apache.org/core/

5. Class 2: Study new computational tools + case studies / benchmarks In class 2 there is less emphasize on the scientific story Examples: – CFD, learn OpenFoam, http://www.opencfd.co.uk/openfoam/ such projects also include learning how to install the tool http://www.opencfd.co.uk/openfoam/

6. Class 3: Porting a scientific problem to another new software Examples: – Program the “Game of Life” in Erlang, UPC, Chapel, Fortress – Port the “Game of Life” to GPGPU – “Game of Life” in Microsoft’s Axum, http://msdn.microsoft.com/en- us/devlabs/dd795202.aspx http://msdn.microsoft.com/en- us/devlabs/dd795202.aspx

7. More topics Develop distributed code for Grid Mathematica or Maple Run your project on Amazon’s EC2 Cloud Find a CPU intensive problem like parameter sweep or Monte Carlo and solve it using Condor Do your project in “R” Do your project using MatlabMPI / pMatlab

8. Cont’ Performance tools: TAU (Tuning and Analysis Utilities), http://www.cs.uoregon.edu/research/tau/ho me.php http://www.cs.uoregon.edu/research/tau/ho me.php

9. 2D Ising Model Simulation DLA – Difussion Limited Aggregation Parallel Sorting algorithms Game: the sesmic duck in OpenMP: http://home.comcast.net/~arch.robison/seism ic_duck.html http://home.comcast.net/~arch.robison/seism ic_duck.html Open|SpeedShop, http://www.openspeedshop.org/wp/ http://www.openspeedshop.org/wp/ – A strong CS background is needed

10. The NAS Parallel Benchmark http://www.nas.nasa.gov/Software/NPB/

11. Parallel Numerical Libraries: Scalapack 1.Download packages. 2.Write an example program. 3.Make benchmarks (speedup & efficiency) Ref: ScaLAPACK: a portable linear algebra for distributed memory computers – design issues and performance. J.Choi et al. Computer Physics Communications 97 (1196) 1-15 http://oscinfo.osc.edu/training/parlib/parlib.ls.pdf

12. Parallel Genetic Algorithms A genetic algorithm (GA) is a search procedure that optimizes some objective function f by maintaining a population P of candidate solutions and employing operations inspired by genetics (called crossover and mutation) to generate a new population from the previous one. Generally, the candidate solutions are encoded as bit strings.

13. Simulated Annealing (SA) Metropolis Algorithm Example: TSP - Traveling Salesman Problem

14. פרוייקט גמר – 12 Fractal Dimension Calculation Using the “Box Counting” Method

15. Neural Networks Parallel (MPI/OpenMP) or Distributed (Condor) Search for a Pattern/Optimization

16. Clustering Parallel (MPI/OpenMP) or Distributed (Condor) Classification of Data using Fuzzy Logic

17. DLA The Diffusion-Limited Aggregation (DLA) is a growth model based on diffusing particles. The growth is started with a single seed A random walker travels about a square lattice; when the walker reaches a site adjacent to the growing cluster it sticks

18. N-Body Problem Using the Barnes-Hut Algorithm An O(n log n) algorithm based on a hierarchical octree representation of space in three dimensions. It computes interactions between distant particles by means of the first order approximation.

19. Multi-Grids Solving the Discrete Poisson Equation using Multigrid Divide-and-Conquer Method

20. Ising Model Spins interactions The Monte Carlo code should be parallel in the sense that each processor will perform work on a separate region of the lattice.

21. Root - Proof http://people.web.psi.ch/feichtinger/doc/pro of_examples.html